Siting of Dark Sky Reserves in China Based on Multi-source Spatial Data and Multiple Criteria Evaluation Method

With the rapid development of population and urbanization and the progress of lighting technology, the influence of artificial light sources has increased. In this context, the problem of light pollution has attracted wide attention. Previous studies have revealed that light pollution can affect biological living environments, human physical and mental health, astronomical observations and many other aspects. Therefore, organizations internationally have begun to advocate for measures to prevent light pollution, many of which are recognized by the International Dark-Sky Association (IDA). In addition to improving public awareness, legal protections, technical treatments and other means, the construction of Dark Sky Reserves (DSR) has proven to be an effective preventive measure. So far, as a pioneer practice in this field, the IDA has identified 11 DSRs worldwide. Based on the DA requirements for DSRs, this paper utilizes NPP-VIIRS nighttime light data and other multi-source spatial data to analyze possible DSR sites in China. The land of China was divided into more than ten thousand 30 km × 30 km fishnets, and constraint and suitable conditions were designated, respectively, as light and cloud conditions, and scale, traffic and attractiveness conditions. Using a multiple criteria evaluation, 1443 fishnets were finally selected as most suitable sites for the construction of DSRs. Results found that less than 25% of China is not subject to light pollution, and less than 13% is suitable for DSR construction, primarily in western and northern areas, including Tibet, Xinjiang, Qinghai, Gansu and Inner Mongolia.

[1]  H. Redkey,et al.  A new approach. , 1967, Rehabilitation record.

[2]  Thomas L. Saaty,et al.  Multicriteria Decision Making: The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation , 1990 .

[3]  Boulder,et al.  The artificial night sky brightness mapped from DMSP satellite Operational Linescan System measurements , 2000, astro-ph/0003412.

[4]  Boulder,et al.  The first World Atlas of the artificial night sky brightness , 2001, astro-ph/0108052.

[5]  P. Cinzano A portable spectrophotometer for light pollution measurements , 2004 .

[6]  S. M. Pauley Lighting for the human circadian clock: recent research indicates that lighting has become a public health issue. , 2004, Medical hypotheses.

[7]  Arunas P. Kuciauskas,et al.  NexSat: Previewing NPOESS/VIIRS Imagery Capabilities , 2006 .

[8]  R. Nelson,et al.  The dark side of light at night: physiological, epidemiological, and ecological consequences , 2007, Journal of pineal research.

[9]  Y. Murayama,et al.  Delineation of Suitable Cropland Areas Using a GIS Based Multi-Criteria Evaluation Approach in the Tam Dao National Park Region, Vietnam , 2010 .

[10]  Donald W. Hillger,et al.  First-Light Imagery from Suomi NPP VIIRS , 2013 .

[11]  Xiaoling Chen,et al.  Satellite-Observed Nighttime Light Variation as Evidence for Global Armed Conflicts , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[12]  Didier Sornette,et al.  Dynamics and spatial distribution of global nighttime lights , 2013, EPJ Data Science.

[13]  Steven D. Miller,et al.  Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band , 2013, Remote. Sens..

[14]  F. Collison,et al.  “Astronomical Tourism”: The Astronomy and Dark Sky Program at Bryce Canyon National Park , 2013 .

[15]  Deren Li,et al.  Can night-time light images play a role in evaluating the Syrian Crisis? , 2014 .

[16]  Jianping Wu,et al.  Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data , 2014, Remote. Sens..

[17]  Jürgen Fischer,et al.  High-Resolution Imagery of Earth at Night: New Sources, Opportunities and Challenges , 2014, Remote. Sens..

[18]  Deidre M. Peroff,et al.  The Sky and Sustainable Tourism Development: A Case Study of a Dark Sky Reserve Implementation in Alqueva , 2015 .

[19]  Wahyu Nurbandi,et al.  Using Visible Infrared Imaging Radiometer Suite (VIIRS) Imagery to identify and analyze light pollution , 2016 .

[20]  Chen Wang,et al.  Assessing Light Pollution in China Based on Nighttime Light Imagery , 2017, Remote. Sens..

[21]  Wei Song,et al.  A New Approach for Detecting Urban Centers and Their Spatial Structure With Nighttime Light Remote Sensing , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[22]  A. Jechow,et al.  Imaging and mapping the impact of clouds on skyglow with all-sky photometry , 2017, Scientific Reports.

[23]  Jun Yang,et al.  Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District , 2018, GIScience & Remote Sensing.

[24]  Andreas Jechow,et al.  Measuring night sky brightness: methods and challenges , 2017, 1709.09558.

[25]  Guojin He,et al.  Potentiality of Using Luojia 1-01 Nighttime Light Imagery to Investigate Artificial Light Pollution , 2018, Sensors.

[26]  Qihao Weng,et al.  A new source of multi-spectral high spatial resolution night-time light imagery—JL1-3B , 2018, Remote Sensing of Environment.

[27]  Juan Wang,et al.  Analysis and simulation of the spatiotemporal evolution pattern of tourism lands at the Natural World Heritage Site Jiuzhaigou, China , 2018, Habitat International.

[28]  K. Baugh,et al.  A simplified model of all-sky artificial sky glow derived from VIIRS Day/Night band data , 2018, Journal of Quantitative Spectroscopy and Radiative Transfer.